Patient reported outcomes: looking beyond the label claim

The use of patient reported outcome scales in clinical trials conducted by the pharmaceutical industry has become more widespread in recent years. The use of such outcomes is particularly common for products developed to treat chronic, disabling conditions where the intention is not to cure but to ameliorate symptoms, facilitate functioning or, ultimately, to improve quality of life. In such cases, patient reported evidence is increasingly viewed as an essential complement to traditional clinical evidence for establishing a product's competitive advantage in the marketplace. In a commercial setting, the value of patient reported outcomes is viewed largely in terms of their potential for securing a labelling claim in the USA or inclusion in the summary of product characteristics in Europe. Although, the publication of the recent US Food and Drug Administration guidance makes it difficult for companies to make claims in the USA beyond symptom improvements, the value of these outcomes goes beyond satisfying requirements for a label claim. The European regulatory authorities, payers both in the US and Europe, clinicians and patients all play a part in determining both the availability and the pricing of medicinal products and all have an interest in patient-reported data that go beyond just symptoms. The purpose of the current paper is to highlight the potential added value of patient reported outcome data currently collected and held by the industry for these groups

Using Multiple Anchor- and Distribution-Based Estimates to Evaluate Clinically Meaningful Change on the Functional Assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) Instrument

Objective: The interpretation of health-related quality of life (HRQL) data from clinical trials can be enhanced by understanding the degree of change in HRQL scores that is considered meaningful. Our objectives were to combine distribution-based and two anchor-based approaches to identify minimally important differences (MIDs) for the 27-item Trial Outcome Index (TOI), the seven-item Social Well-Being (SWB) subscale, and the six-item Emotional Well-being (EWB) subscale from the Functional Assessment of Cancer Therapy-Biological Response Modifiers (FACT-BRM) instrument. Methods: Distribution-based MIDs were based on the standard error of measurement. Anchor-based approaches utilized patient-reported global rating of change (GRC) and change in physician-reported performance status rating (PSR). Correlations and weighted kappa statistics were used to assess association and agreement between the two anchors. FACT-BRM changes were evaluated for three time periods: baseline to month 1, month 2 to month 3, and month 5 to month 6. Results: Association between GRC and change in PSR was poor. Correlation between the anchors and HRQL change scores was largest at month 1 and decreased through month 6. Combining results from all approaches, the MIDs identified were 5–8 points for the TOI, 2 points for the SWB subscale, and 2–3 points for the EWB subscale. Conclusions: We combined patient-reported estimates, physician-reported estimates, and distribution-based estimates to derive MIDs for HRQL outcomes from the FACT-BRM. These results will enable interpretation of treatment group effects in a clinical trial setting, and they can be used to estimate sample size or power when designing future studies

Patient-Reported Outcomes in Cancer Drug Development and US Regulatory Review: Perspectives From Industry, the Food and Drug Administration, and the Patient

Data reported directly by patients about how they feel and function are rarely included in oncology drug labeling in the United States, in contrast to Europe and to nononcology labeling in the United States, where this practice is more common. Multiple barriers exist, including challenges unique to oncology trials, and industry's concerns regarding cost, logistical complexities, and the Food and Drug Administration's (FDA's) rigorous application of its 2009 guidance on the use of patient-reported outcome (PRO) measures. A panel consisting of representatives of industry, FDA, the PRO Consortium, clinicians, and patients was assembled at a 2014 workshop cosponsored by FDA to identify practical recommendations for overcoming these barriers. Key recommendations included increasing proactive encouragement by FDA to clinical trial sponsors for including PROs in drug development programs; provision of comprehensive PRO plans by sponsors to FDA early in drug development; promotion of an oncology-specific PRO research agenda; development of an approach to existing ("legacy") PRO measures, when appropriate (focused initially on symptoms and functional status); and increased FDA and industry training in PRO methodology. FDA has begun implementing several of these recommendations

Assessing changes in chronic spontaneous/idiopathic urticaria: comparisons of patient-reported outcomes using latent growth modeling

Introduction Assessing the consequences of chronic spontaneous/idiopathic urticaria (CSU) requires the evaluation of health-related quality of life (HRQoL) associated with the severity of CSU signs and symptoms. It is important to understand how signs, symptoms, and HRQoL change over time in CSU. Evidence is lacking on how closely changes in signs and symptoms of CSU are related to changes in HRQoL. The objective of this study was to assess the correlation between changes in patient-reported outcome measures (PROMs) of signs and symptoms, dermatologic quality of life (QoL), and urticaria-specific QoL. Methods Latent growth models (LGMs) were applied to longitudinal data from three randomized, Phase 3 clinical trials investigating the efficacy and safety of omalizumab in CSU. Results A near-perfect association between changes in signs and symptoms and changes in dermatologic and urticaria-specific QoLs was identified in each clinical trial when using LGMs (correlation coefficient range 0.88–0.92). Conclusion Evidence showed that changes in signs and symptoms are closely related to changes in HRQoL. However, analyses were performed on clinical trial results of an extremely effective treatment; a less effective treatment with much smaller changes over time may not show such close correlations. Results suggest that any of these PROMs may be used to understand changes in CSU